Ethnicity-specific epigenetic variation in naïve CD4+ T cells and the susceptibility to autoimmunity

Epigenetics & Chromatin

Amr H. Sawalha⁴  Jonathan D. Wren¹  Kathleen Maksimowicz-McKinnon²  Elizabeth Gensterblum³  Mikhail Ognenovski³  Patrick Coit³ 

[1] Department of Biochemistry and Molecular Biology, The University of Oklahoma Health Sciences Center, 1100 N Lindsay Ave, Oklahoma City 73104, OK, USA;Division of Rheumatology, Henry Ford Health System, 3031 W Grand Blvd, Detroit 48202, MI, USA;Division of Rheumatology, University of Michigan, 5520 MSRB-1, SPC 5680, 1150 W. Medical Center Drive, Ann Arbor 48109, MI, USA;Center for Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Ave, #2017, Ann Arbor 48109, MI, USA

关键词: T cell;    Genetic;    Ethnicity specific;    Lupus;    Autoimmunity;    Epigenetic;   

Others  :  1234467
DOI  :  10.1186/s13072-015-0037-1

 received in 2015-10-03, accepted in 2015-10-14,  发布年份 2015

【 摘 要 】

Background

Genetic and epigenetic variability contributes to the susceptibility and pathogenesis of autoimmune diseases. T cells play an important role in several autoimmune conditions, including lupus, which is more common and more severe in people of African descent. To investigate inherent epigenetic differences in T cells between ethnicities, we characterized genome-wide DNA methylation patterns in naïve CD4+ T cells in healthy African-Americans and European-Americans, and then confirmed our findings in lupus patients.

Results

Impressive ethnicity-specific clustering of DNA methylation profiling in naïve CD4+ T cells was revealed. Hypomethylated loci in healthy African-Americans were significantly enriched in pro-apoptotic and pro-inflammatory genes. We also found hypomethylated genes in African-Americans to be disproportionately related to autoimmune diseases including lupus. We then confirmed that these genes, such as IL32, CD226, CDKN1A, and PTPRN2 were similarly hypomethylated in lupus patients of African-American compared to European-American descent. Using patch DNA methylation and luciferase reporter constructs, we showed that methylation of the IL32 promoter region reduces gene expression in vitro. Importantly, bisulfite DNA sequencing demonstrated that cis-acting genetic variants within and directly disrupting CpG sites account for some ethnicity-specific variability in DNA methylation.

Conclusion

Ethnicity-specific inherited epigenetic susceptibility loci in CD4+ T cells provide clues to explain differences in the susceptibility to autoimmunity and possibly other T cell-related diseases between populations.

【 授权许可】

   
2015 Coit et al.

【 图 表 】

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【 参考文献 】

• [1]Fraga MF, Ballestar E, Paz MF, Ropero S, Setien F, Ballestar ML et al.. Epigenetic differences arise during the lifetime of monozygotic twins. Proc Natl Acad Sci USA. 2005; 102(30):10604-10609.
• [2]Cooper GS, Stroehla BC. The epidemiology of autoimmune diseases. Autoimmun Rev. 2003; 2(3):119-125.
• [3]Somers EC, Marder W, Cagnoli P, Lewis EE, DeGuire P, Gordon C et al.. Population-based incidence and prevalence of systemic lupus erythematosus: the Michigan Lupus Epidemiology and Surveillance program. Arthritis Rheumatol. 2014; 66(2):369-378.
• [4]Zhang FF, Cardarelli R, Carroll J, Fulda KG, Kaur M, Gonzalez K et al.. Significant differences in global genomic DNA methylation by gender and race/ethnicity in peripheral blood. Epigenetics. 2014; 6(5):623-629.
• [5]Heyn H, Moran S, Hernando-Herraez I, Sayols S, Gomez A, Sandoval J et al.. DNA methylation contributes to natural human variation. Genome Res. 2013; 23(9):1363-1372.
• [6]Coit P, Jeffries M, Altorok N, Dozmorov MG, Koelsch KA, Wren JD et al.. Genome-wide DNA methylation study suggests epigenetic accessibility and transcriptional poising of interferon-regulated genes in naive CD4+ T cells from lupus patients. J Autoimmun. 2013; 43:78-84.
• [7]Coit P, Renauer P, Jeffries MA, Merrill JT, McCune WJ, Maksimowicz-McKinnon K et al.. Renal involvement in lupus is characterized by unique DNA methylation changes in naive CD4+ T cells. J Autoimmun. 2015; 61:29-35.
• [8]Diez-Guerra FJ. Neurogranin, a link between calcium/calmodulin and protein kinase C signaling in synaptic plasticity. IUBMB Life. 2010; 62(8):597-606.
• [9]Huffman DL, O’Halloran TV. Function, structure, and mechanism of intracellular copper trafficking proteins. Annu Rev Biochem. 2001; 70:677-701.
• [10]Alonso A, Sasin J, Bottini N, Friedberg I, Friedberg I, Osterman A et al.. Protein tyrosine phosphatases in the human genome. Cell. 2004; 117(6):699-711.
• [11]Wren JD. Extending the mutual information measure to rank inferred literature relationships. BMC Bioinform. 2004; 5:145. BioMed Central Full Text
• [12]Wren JD, Garner HR. Shared relationship analysis: ranking set cohesion and commonalities within a literature-derived relationship network. Bioinformatics. 2004; 20(2):191-198.
• [13]Wren JD, Bekeredjian R, Stewart JA, Shohet RV, Garner HR. Knowledge discovery by automated identification and ranking of implicit relationships. Bioinformatics. 2004; 20(3):389-398.
• [14]Wren JD. A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide. Bioinformatics. 2009; 25(13):1694-1701.
• [15]Bestor TH. The DNA methyltransferases of mammals. Hum Mol Genet. 2000; 9(16):2395-2402.
• [16]Shoemaker R, Deng J, Wang W, Zhang K. Allele-specific methylation is prevalent and is contributed by CpG-SNPs in the human genome. Genome Res. 2010; 20(7):883-889.
• [17]Devireddy LR, Green MR. Transcriptional program of apoptosis induction following interleukin 2 deprivation: identification of RC3, a calcium/calmodulin binding protein, as a novel proapoptotic factor. Mol Cell Biol. 2003; 23(13):4532-4541.
• [18]Moulton VR, Tsokos GC. T cell signaling abnormalities contribute to aberrant immune cell function and autoimmunity. J Clin Invest. 2015; 125(6):2220-2227.
• [19]Li S, Jiang W, Xiong Y, Wang X, Li Y, Shen S et al.. Neurogranin overexpression on peripheral blood mononuclear cells from patients with systemic lupus erythematosus. Chin J Rheumatol. 2008; 12(4):265-268.
• [20]Luo X, He X, Wu C, Ni J. Dong Ll, Li S. The discovery of novel splicing variants of neurogranin and their role in the pathogenesis of systemic lupus erythematosus. Arthritis Rheumatol. 2014; 66(10 (Supplement)):S1173-S1174.
• [21]Pan G, O’Rourke K, Chinnaiyan AM, Gentz R, Ebner R, Ni J et al.. The receptor for the cytotoxic ligand TRAIL. Science. 1997; 276(5309):111-113.
• [22]Kim SH, Han SY, Azam T, Yoon DY, Dinarello CA. Interleukin-32: a cytokine and inducer of TNFalpha. Immunity. 2005; 22(1):131-142.
• [23]Goda C, Kanaji T, Kanaji S, Tanaka G, Arima K, Ohno S et al.. Involvement of IL-32 in activation-induced cell death in T cells. Int Immunol. 2006; 18(2):233-240.
• [24]Dhir V, Singh AP, Aggarwal A, Naik S, Misra R. Increased T-lymphocyte apoptosis in lupus correlates with disease activity and may be responsible for reduced T-cell frequency: a cross-sectional and longitudinal study. Lupus. 2009; 18(9):785-791.
• [25]Rebbeck TR. Molecular epidemiology of the human glutathione S-transferase genotypes GSTM1 and GSTT1 in cancer susceptibility. Cancer Epidemiol Biomark Prev. 1997; 6(9):733-743.
• [26]Lofgren SE, Delgado-Vega AM, Gallant CJ, Sanchez E, Frostegard J, Truedsson L et al.. A 3′-untranslated region variant is associated with impaired expression of CD226 in T and natural killer T cells and is associated with susceptibility to systemic lupus erythematosus. Arthritis Rheum. 2010; 62(11):3404-3414.
• [27]Chung SA, Tian C, Taylor KE, Lee AT, Ortmann WA, Hom G et al.. European population substructure is associated with mucocutaneous manifestations and autoantibody production in systemic lupus erythematosus. Arthritis Rheum. 2009; 60(8):2448-2456.
• [28]Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD et al.. Minfi: a flexible and comprehensive bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics. 2014; 30(10):1363-1369.
• [29]Team RC. R: A language and environment for statistical computing. 2014.
• [30]Jeffrey T. Leek WEJ, Hilary S. Parker, Elana J. Fertig, Andrew E. Jaffe, John D. Storey. sva: Surrogate Variable Analysis.
• [31]da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009; 4(1):44-57.
• [32]da Huang W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009; 37(1):1-13.
• [33]Lewin J, Schmitt AO, Adorjan P, Hildmann T, Piepenbrock C. Quantitative DNA methylation analysis based on four-dye trace data from direct sequencing of PCR amplificates. Bioinformatics. 2004; 20(17):3005-3012.